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| 000_appetite_whetting_1.pdf |
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| 000b_appetite_whetting_2.pdf |
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| 001_context.pdf |
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| 002_dimensions.pdf |
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| 003_this_course_1.pdf |
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| 004_this_course_2.pdf |
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| 005_escience.pdf |
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| 006_big_data.pdf |
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| 007_logistics.pdf |
345.23Кб |
| 008_data_models.pdf |
620.24Кб |
| 009_relational_motivation.pdf |
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| 010_relational_algebra_intro.pdf |
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| 011.5_relational_algebra_union_diff_select.pdf |
364.37Кб |
| 011.6_relational_algebra_project_cross_equijoin.pdf |
380.76Кб |
| 011.7_theta_join.pdf |
492.09Кб |
| 011.8_interpreting_complicated_sql.pdf |
577.04Кб |
| 011.9_user_defined_functions.pdf |
61.58Кб |
| 012_physical_optimization.pdf |
427.16Кб |
| 013_declarative_languages.pdf |
661.33Кб |
| 014_logical_data_independence.pdf |
468.99Кб |
| 015_scalability.pdf |
223.89Кб |
| 016_parallel_thinking.pdf |
3.11Мб |
| 017_map_reduce_abstraction.pdf |
2.18Мб |
| 018_map_reduce_pseudocode.pdf |
94.11Кб |
| 019_map_reduce_text_examples.pdf |
337.57Кб |
| 020_map_reduce_join_social_examples.pdf |
326.08Кб |
| 021_map_reduce_matrix_multiply.pdf |
318.03Кб |
| 022_map_reduce_implementation_overview.pdf |
500.90Кб |
| 023_parallel_databases.pdf |
385.47Кб |
| 024_mapreduce_and_databases.pdf |
94.87Кб |
| 025_mapreduce_and_databases_experiments.pdf |
730.08Кб |
| 026_nosql_intro.pdf |
525.15Кб |
| 027_eventual_consistency.pdf |
717.72Кб |
| 028_memcached.pdf |
585.81Кб |
| 029_dynamo.pdf |
466.19Кб |
| 030_couchdb.pdf |
562.20Кб |
| 031_bigtable.pdf |
483.18Кб |
| 032_other_google_systems.pdf |
728.87Кб |
| 033_nosql_response.pdf |
746.59Кб |
| 034_pig_intro.pdf |
527.08Кб |
| 035_pig_load_filter_group_foreach.pdf |
191.03Кб |
| 036_cogroup_join.pdf |
233.74Кб |
| 037_pig_evaluation.pdf |
336.05Кб |
| 038_stats_intro.pdf |
148.64Кб |
| 039_publication_bias.pdf |
408.27Кб |
| 040_effect_size_meta_analysis_heteroskedasticity.pdf |
568.00Кб |
| 041_fraud_benfords_law.pdf |
1.22Мб |
| 042_multiple_hypothesis_testing_CORRECTED.pdf |
467.45Кб |
| 043_recap_and_big_data.pdf |
659.37Кб |
| 044_intro_bayesian.pdf |
103.51Кб |
| 045_bayes_rule.pdf |
409.41Кб |
| 047_overview_machine_learning.pdf |
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| 048_intro_machine_learning_2.pdf |
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| 049_rules_1.pdf |
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| 050_rules_2.pdf |
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| 051_intro_trees.pdf |
476.63Кб |
| 052_information_gain.pdf |
418.71Кб |
| 053_overfitting.pdf |
346.55Кб |
| 054_evaluation_thresholds.pdf |
270.59Кб |
| 055_bootstrap.pdf |
284.71Кб |
| 056_ensembles_and_boosting.pdf |
242.18Кб |
| 057_random_forests.pdf |
87.54Кб |
| 058_nearest_neighbor.pdf |
187.86Кб |
| 059_gradient_descent_part_1.pdf |
1.36Мб |
| 060_gradient_descent_part_2.pdf |
595.09Кб |
| 061_intuition_logistic_regression_svms.pdf |
640.32Кб |
| 062_intuition_regularization.pdf |
490.13Кб |
| 063_stochastic_gradient_descent.pdf |
490.33Кб |
| 064_unsupervised_learning_copy.pdf |
550.94Кб |
| 065_kmeans.pdf |
181.16Кб |
| 066_dbscan.pdf |
636.50Кб |
| 077b_graph_histograms.pdf |
481.81Кб |
| 078_structural_analysis_tasks.pdf |
398.83Кб |
| 079_pagerank.pdf |
278.59Кб |
| 080_traversal_tasks.pdf |
399.97Кб |
| 081_pattern_matching.pdf |
467.50Кб |
| 082_relational_algebra_for_graph_tasks.pdf |
91.43Кб |
| 083_prism_example.pdf |
147.04Кб |
| 084_evaluating_recursive_programs.pdf |
576.99Кб |
| 085_optimizing_recursive_programs_in_mr.pdf |
437.88Кб |
| 086_graph_representations.pdf |
423.76Кб |
| 087_pagerank_mapreduce_pregel.pdf |
803.64Кб |
| 1_instructions.pdf |
260.96Кб |
| 10 - 1 - 01 Guest Segment Aaron Kimball Wibidata.mp4 |
21.26Мб |
| 10 - 2 - 02 Guest Segment Karen Hsu Datameer.mp4 |
12.93Мб |
| 1 - 10 - Logistics (742).mp4 |
10.90Мб |
| 1 - 10 - Logistics (742).srt |
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| 1 - 11 - Twitter Assignment Getting Started with Problem 0 and Problem 1.mp4 |
25.30Мб |
| 1 - 1 - Appetite Whetting Part 1 (1538).mp4 |
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| 1 - 1 - Appetite Whetting Part 1 (1538).srt |
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| 1 - 2 - Appetite Whetting Part 2 (1344).mp4 |
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| 1 - 2 - Appetite Whetting Part 2 (1344).srt |
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| 1 - 3 - Context (930).mp4 |
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| 1 - 3 - Context (930).srt |
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| 1 - 4 - Dimensions (1024).mp4 |
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| 1 - 4 - Dimensions (1024).srt |
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| 1 - 5 - This Course Part 1 (1402).mp4 |
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| 1 - 5 - This Course Part 1 (1402).srt |
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| 1 - 6 - This Course Part 2 (1050).mp4 |
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| 1 - 7 - eScience (1146).mp4 |
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| 1 - 7 - eScience (1146).srt |
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| 1 - 8 - Big Data (1436).mp4 |
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| 1 - 8 - Big Data (1436).srt |
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| 1 - 9 - Guest Lecture Biomedical Informatics (1024).mp4 |
17.23Мб |
| 1 - 9 - Guest Lecture Biomedical Informatics (1024).srt |
12.97Кб |
| 2_instructions.pdf |
195.44Кб |
| 2 - 10 - Declarative Languages (1030).mp4 |
15.28Мб |
| 2 - 10 - Declarative Languages (1030).srt |
14.06Кб |
| 2 - 11 - Logical Data Independence (1123).mp4 |
14.02Мб |
| 2 - 11 - Logical Data Independence (1123).srt |
14.65Кб |
| 2 - 1 - From Data Models to Databases (1035).mp4 |
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| 2 - 1 - From Data Models to Databases (1035).srt |
17.80Кб |
| 2 - 2 - Motivating Relational Algebra (857).mp4 |
12.66Мб |
| 2 - 2 - Motivating Relational Algebra (857).srt |
13.35Кб |
| 2 - 3 - Relational Algebra Introduction (1058).mp4 |
15.77Мб |
| 2 - 3 - Relational Algebra Introduction (1058).srt |
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| 2 - 4 - Relational Algebra Details Union Diff Select (1053).mp4 |
15.86Мб |
| 2 - 4 - Relational Algebra Details Union Diff Select (1053).srt |
15.37Кб |
| 2 - 5 - Relational Algebra Details Project Cross Product Equi-Join (1106).mp4 |
16.07Мб |
| 2 - 5 - Relational Algebra Details Project Cross Product Equi-Join (1106).srt |
15.22Кб |
| 2 - 6 - Relational Algebra Details Theta-Join (834).mp4 |
12.20Мб |
| 2 - 6 - Relational Algebra Details Theta-Join (834).srt |
12.32Кб |
| 2 - 7 - SQL for Data Science Interpreting Complicated SQL (1212).mp4 |
18.23Мб |
| 2 - 7 - SQL for Data Science Interpreting Complicated SQL (1212).srt |
18.60Кб |
| 2 - 8 - SQL for Data Science User-Defined Functions (759).mp4 |
11.16Мб |
| 2 - 8 - SQL for Data Science User-Defined Functions (759).srt |
11.12Кб |
| 2 - 9 - Physical Optimization (1114).mp4 |
16.04Мб |
| 2 - 9 - Physical Optimization (1114).srt |
16.54Кб |
| 3_js_quiz.pdf |
255.42Кб |
| 3_python_instructions.pdf |
142.29Кб |
| 3 - 10 - Comparing MapReduce and Databases (0639).mp4 |
8.95Мб |
| 3 - 10 - Comparing MapReduce and Databases (0639).srt |
11.06Кб |
| 3 - 11 - Experimental Results MR and DB (1501).mp4 |
20.16Мб |
| 3 - 11 - Experimental Results MR and DB (1501).srt |
19.72Кб |
| 3 - 1 - Scalability Basics (1618).mp4 |
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| 3 - 1 - Scalability Basics (1618).srt |
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| 3 - 2 - Parallel Processing Patterns (1126).mp4 |
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| 3 - 2 - Parallel Processing Patterns (1126).srt |
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| 3 - 3 - MapReduce Abstractions (1117).mp4 |
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| 3 - 3 - MapReduce Abstractions (1117).srt |
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| 3 - 4 - MapReduce Pseudocode (754).mp4 |
12.28Мб |
| 3 - 4 - MapReduce Pseudocode (754).srt |
10.26Кб |
| 3 - 5 - MapReduce Text Examples (958).mp4 |
16.16Мб |
| 3 - 5 - MapReduce Text Examples (958).srt |
12.98Кб |
| 3 - 6 - MapReduce Relational Join Social Example (1317).mp4 |
18.74Мб |
| 3 - 6 - MapReduce Relational Join Social Example (1317).srt |
17.75Кб |
| 3 - 7 - MapReduce Matrix Multiply Example (931).mp4 |
13.20Мб |
| 3 - 7 - MapReduce Matrix Multiply Example (931).srt |
10.01Кб |
| 3 - 8 - MapReduce Implementation Overview (1338).mp4 |
18.03Мб |
| 3 - 8 - MapReduce Implementation Overview (1338).srt |
19.71Кб |
| 3 - 9 - Parallel Databases (1618).mp4 |
22.69Мб |
| 3 - 9 - Parallel Databases (1618).srt |
24.28Кб |
| 4_aws-setup.pdf |
270.41Кб |
| 4_quiz.pdf |
257.76Кб |
| 4 - 1 - Statistics Intro (1036).mp4 |
16.87Мб |
| 4 - 1 - Statistics Intro (1036).srt |
15.54Кб |
| 4 - 2 - Publication Bias (845).mp4 |
13.01Мб |
| 4 - 2 - Publication Bias (845).srt |
12.10Кб |
| 4 - 3 - Effect Size Meta-analysis Heteroskedasticity (931).mp4 |
14.14Мб |
| 4 - 3 - Effect Size Meta-analysis Heteroskedasticity (931).srt |
14.23Кб |
| 4 - 4 - Fraud and Benfords Law (1055).mp4 |
15.98Мб |
| 4 - 4 - Fraud and Benfords Law (1055).srt |
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| 4 - 5 - Multiple Hypothesis Testing (1122).mp4 |
16.53Мб |
| 4 - 5 - Multiple Hypothesis Testing (1122).srt |
15.51Кб |
| 4 - 6 - Recap and Big Data (1139).mp4 |
17.50Мб |
| 4 - 6 - Recap and Big Data (1139).srt |
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| 4 - 7 - Bayesian Intro (759).mp4 |
12.51Мб |
| 4 - 7 - Bayesian Intro (759).srt |
10.81Кб |
| 4 - 8 - Bayes Rule (1153).mp4 |
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| 4 - 8 - Bayes Rule (1153).srt |
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| 5 - 10 - 10 Ensembles Bagging and Boosting (0919).mp4 |
13.83Мб |
| 5 - 10 - 10 Ensembles Bagging and Boosting (0919).srt |
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| 5 - 1 - 01 Introduction to Machine Learning Part 1 (0754).mp4 |
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| 5 - 1 - 01 Introduction to Machine Learning Part 1 (0754).srt |
12.31Кб |
| 5 - 11 - 11 Random Forests (1116).mp4 |
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| 5 - 11 - 11 Random Forests (1116).srt |
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| 5 - 12 - 12 k Nearest Neighbors (1143).mp4 |
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| 5 - 12 - 12 k Nearest Neighbors (1143).srt |
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| 5 - 2 - 02 Introduction to Machine Learning Part 2 (0523).mp4 |
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| 5 - 2 - 02 Introduction to Machine Learning Part 2 (0523).srt |
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| 5 - 3 - 03 Rules Part 1 (0919).mp4 |
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| 5 - 3 - 03 Rules Part 1 (0919).srt |
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| 5 - 4 - 04 Rules Part 2 (0539).mp4 |
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| 5 - 4 - 04 Rules Part 2 (0539).srt |
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| 5 - 5 - 05 Decision Trees Entropy (1051).mp4 |
15.72Мб |
| 5 - 5 - 05 Decision Trees Entropy (1051).srt |
14.15Кб |
| 5 - 6 - 06 Information Gain (1143).mp4 |
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| 5 - 6 - 06 Information Gain (1143).srt |
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| 5 - 7 - 07 Overfitting (1104).mp4 |
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| 5 - 7 - 07 Overfitting (1104).srt |
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| 5 - 8 - 08 Evaluation and Cross-Validation (1046).mp4 |
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| 5 - 8 - 08 Evaluation and Cross-Validation (1046).srt |
15.06Кб |
| 5 - 9 - 09 The Bootstrap (0413).mp4 |
6.64Мб |
| 5 - 9 - 09 The Bootstrap (0413).srt |
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| 6_VisualizationAssignment.twbx |
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| 6 - 10 - 10 Evaluation (325).mp4 |
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| 6 - 10 - 10 Evaluation (325).srt |
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| 6 - 1 - 01 Introduction (717).mp4 |
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| 6 - 1 - 01 Introduction (717).srt |
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| 6 - 2 - 02 Data Types (937).mp4 |
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| 6 - 2 - 02 Data Types (937).srt |
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| 6 - 3 - 03 Data Types (Exercises) (407).mp4 |
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| 6 - 3 - 03 Data Types (Exercises) (407).srt |
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| 6 - 4 - 04 Data Dimensions (308).mp4 |
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| 6 - 4 - 04 Data Dimensions (308).srt |
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| 6 - 5 - 05 Visual Encoding (Part 1) (638).mp4 |
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| 6 - 5 - 05 Visual Encoding (Part 1) (638).srt |
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| 6 - 6 - 06 Visual Encoding (Part 2) (254).mp4 |
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| 6 - 6 - 06 Visual Encoding (Part 2) (254).srt |
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| 6 - 7 - 07 Visual Perception (Part 1) (439).mp4 |
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| 6 - 7 - 07 Visual Perception (Part 1) (439).srt |
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| 6 - 8 - 08 Visual Perception (Part 2) (418).mp4 |
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| 6 - 8 - 08 Visual Perception (Part 2) (418).srt |
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| 6 - 9 - 09 Visual Perception (Part 3) (356).mp4 |
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| 6 - 9 - 09 Visual Perception (Part 3) (356).srt |
4.41Кб |
| 7 - 10 - 10 Optimizing MapReduce for Graph Traversal (0820).mp4 |
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| 7 - 1 - 01 Graph Basics (0622).mp4 |
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| 7 - 11 - 11 Graph Representations (0651).mp4 |
9.66Мб |
| 7 - 12 - 12 PageRank in MapReduce and Pregel (1042).mp4 |
15.04Мб |
| 7 - 2 - 02 Structure Degree Histograms (0814).mp4 |
11.81Мб |
| 7 - 3 - 03 Structure Diameter Connectivity Centrality (0656).mp4 |
9.62Мб |
| 7 - 4 - 04 Traversal PageRank (0637).mp4 |
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| 7 - 5 - 05 Traversal Spanning Trees Circuits Flows (0657).mp4 |
10.30Мб |
| 7 - 6 - 06 Patterns Triangles SPARQL Datalog (1002).mp4 |
13.90Мб |
| 7 - 7 - 07 Patterns Relational Algebra for Graph Query (0826).mp4 |
11.97Мб |
| 7 - 8 - 08 PRISM Example in Datalog (1110).mp4 |
16.20Мб |
| 7 - 9 - 09 Evaluating Graph Traversal Queries (0829).mp4 |
11.59Мб |
| 8 - 10 - Pig Functions (1141).mp4 |
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| 8 - 10 - Pig Functions (1141).srt |
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| 8 - 11 - Pig Join and Co-Group Join (1610).mp4 |
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| 8 - 11 - Pig Join and Co-Group Join (1610).srt |
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| 8 - 12 - Pig Evaluation (1011).mp4 |
14.38Мб |
| 8 - 12 - Pig Evaluation (1011).srt |
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| 8 - 1 - NoSQL Introduction (830).mp4 |
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| 8 - 1 - NoSQL Introduction (830).srt |
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| 8 - 2 - Eventual Consistency (1856).mp4 |
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| 8 - 2 - Eventual Consistency (1856).srt |
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| 8 - 3 - Example Memcached (1637).mp4 |
23.31Мб |
| 8 - 3 - Example Memcached (1637).srt |
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| 8 - 4 - Example Dynamo (1016).mp4 |
13.78Мб |
| 8 - 4 - Example Dynamo (1016).srt |
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| 8 - 5 - Example CouchDB (1000).mp4 |
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| 8 - 5 - Example CouchDB (1000).srt |
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| 8 - 6 - Example BigTable (1105).mp4 |
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| 8 - 6 - Example BigTable (1105).srt |
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| 8 - 7 - Example Other Google Systems (1618).mp4 |
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| 8 - 7 - Example Other Google Systems (1618).srt |
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| 8 - 8 - Response to NoSQL Systems (1444).mp4 |
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| 8 - 8 - Response to NoSQL Systems (1444).srt |
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| 8 - 9 - Pig Intro (1202).mp4 |
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| 8 - 9 - Pig Intro (1202).srt |
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| 9 - 1 - 01 Gradient Descent Part 1 (0718).mp4 |
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| 9 - 1 - 01 Gradient Descent Part 1 (0718).srt |
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| 9 - 2 - 02 Gradient Descent Part 2 (0629).mp4 |
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| 9 - 2 - 02 Gradient Descent Part 2 (0629).srt |
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| 9 - 3 - 03 Intuition for Logistic Regression and Support Vector Machines (1055).mp4 |
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| 9 - 3 - 03 Intuition for Logistic Regression and Support Vector Machines (1055).srt |
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| 9 - 4 - 04 Intuition for Regularization (0659).mp4 |
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| 9 - 4 - 04 Intuition for Regularization (0659).srt |
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| 9 - 5 - 05 Stochastic Gradient Descent Minibatches Parallelization (0853).mp4 |
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| 9 - 5 - 05 Stochastic Gradient Descent Minibatches Parallelization (0853).srt |
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| 9 - 6 - 06 Unsupervised Learning (0611).mp4 |
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| 9 - 6 - 06 Unsupervised Learning (0611).srt |
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| 9 - 7 - 07 K-means (0556).mp4 |
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| 9 - 7 - 07 K-means (0556).srt |
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| 9 - 8 - 08 DBSCAN (0913).mp4 |
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| 9 - 8 - 08 DBSCAN (0913).srt |
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| Class Virtual Machine.pdf |
88.58Кб |
| Course Logistics.pdf |
123.80Кб |
| Coursera-Data-Science-Ubuntu.ova |
2.34Гб |
| Github Instructions.pdf |
127.83Кб |
| guests-datameer_beyond_mapreduce.pdf |
188.82Кб |
| guests-kiji-uw-data-science.pdf |
736.07Кб |
| Infovis Aragon 10 Evaluation.pdf |
298.38Кб |
| Infovis Aragon 1 Introduction.pdf |
673.51Кб |
| Infovis Aragon 2 Data Types.pdf |
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| Infovis Aragon 3 Data Types (Exercises).pdf |
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| Infovis Aragon 4 Data Dimensions.pdf |
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| Infovis Aragon 5 Visual Encoding (Part 1).pdf |
750.04Кб |
| Infovis Aragon 6 Visual Encoding (Part 2).pdf |
685.36Кб |
| Infovis Aragon 7 Visual Perception (Part 1).pdf |
884.68Кб |
| Infovis Aragon 8 Visual Perception (Part 2).pdf |
449.81Кб |
| Infovis Aragon 9 Visual Perception (Part 3).pdf |
330.23Кб |
| Introduction to JSMapreduce.mp4 |
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| Python Resources.pdf |
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| Running Tableau on AWS.pdf |
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| Syllabus.pdf |
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| TableauDesktop.exe |
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| tips.txt |
856б |